speech production deficits in early readers: predictors of risk

Speech production deficits in early readers:predictors of risk

Judith G. Foy · Virginia A. Mann

Published online: 17 February 2011

© The Author(s) 2011. This article is published with open access at Springerlink.com

Abstract Speech problems and reading disorders are linked, suggesting that

speech problems may potentially be an early marker of later difficulty in associating

graphemes with phonemes. Current norms suggest that complete mastery of the

production of the consonant phonemes in English occurs in most children at around

6–7 years. Many children enter formal schooling (kindergarten) around 5 years of

age with near-adult levels of speech production. Given that previous research has

shown that speech production abilities and phonological awareness skills are linked

in preschool children, we set out to examine whether this pattern also holds for

children just beginning to learn to read, as suggested by the critical age hypothesis.In the present study, using a diverse sample, we explored whether expressive

phonological skills in 92 5-year-old children at the beginning and end of kinder-

garten were associated with early reading skills. Speech errors were coded

according to whether they were developmentally appropriate, position within the

syllable, manner of production of the target sounds, and whether the error involved a

substitution, omission, or addition of a speech sound. At the beginning of the school

year, children with significant early reading deficits on a predictively normed test

(DIBELS) made more speech errors than children who were at grade level. Most of

these errors were typical of kindergarten children (e.g., substitutions involving

fricatives), but reading-delayed children made more of these errors than children

who entered kindergarten with grade level skills. The reading-delayed children also

made more atypical errors, consistent with our previous findings about preschoolers.

J. G. Foy (&)

Department of Psychology, Loyola Marymount University,

1 LMU Drive, Los Angeles, CA 90045, USA

e-mail: [email protected]

V. A. Mann

University of California, 3151 Social Sciences Plaza, Irvine, CA 92697-5100, USA

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Read Writ (2012) 25:799–830

DOI 10.1007/s11145-011-9300-4

Children who made no speech errors at the beginning of kindergarten had superior

early reading abilities, and improvements in speech errors over the course of the

year were significantly correlated with year-end reading skills. The role of

expressive vocabulary and working memory were also explored, and appear to

account for some of these findings.

Keywords Early reading · Letter knowledge · Phonemic awareness ·

Speech production

Introduction

Reading impairment is now well known to be closely associated with impaired

phoneme processing (Goswami & Bryant, 1990). Children with weak phonological

processing skills are highly likely to have or to develop later reading problems

(Vellutino, Scanlon, Small, & Fanuele, 2006), and children with diagnosed speech

and language disorders are more likely than children without these difficulties to

have later reading problems (Catts, 1993). What is less understood is how speech

problems might link to reading problems.

The literature consistently links reading difficulty to speech production deficits,

but what may be key is the development of strong expressive speech skills by the

time the child begins to learn to read. For example, in support of their critical agehypothesis, Bishop and Adams (1990) showed that children whose speech

impairments had resolved by age 5½ years were not at significant risk for later

reading problems compared to children whose speech problems persisted by the

time they entered school. This finding has been corroborated in an important series

of studies further showing that preschool speech problems are more predictive of

later reading problems if they persist into the early school years (Leitao & Fletcher,

2004; Nathan, Stackhouse, Goulandris, & Snowling, 2004a, b).

In support of the phoneme-early reading link, poor readers have difficulties with

the repetition of multisyllabic words (Snowling, 1981), nonwords (Snowling,

Goulandris, Bowlby, & Howell, 1986), and phonologically complex phrases (Catts,

1986). The phonological processing deficits associated with reading problems

include impaired categorization of speech sounds (Serniclaes, Van Heghe, Mousty,

Carre, & Sprenger-Charolles, 2004). For example, studies of categorization and

discrimination (Tallal & Piercy, 1974; Werker & Tees, 1987) indicate that poor

readers exhibit difficulty perceiving differences between stop consonants such as /d/

and /b/ in syllables such as /da/ and /ba/. Even 2-month old infants at familial risk

for dyslexia fail to discriminate between words differing in initial stop consonants

where other infants succeed (e.g., /b/ and /d/; Van Leeuwen et al., 2007). These

observations about the link between speech problems and reading problems have

been hypothesized to reflect phoneme representations that are fuzzy and difficult to

associate with their related graphemes (e.g., Catts, Fey, Zhang, & Tomblin, 2001;

Fowler, 1991; Metsala, 1997; Swan & Goswami, 1997; Vellutino et al., 2006).

If poor readers do have impoverished phonological representations, then it would

be expected that they would show deficits not only in tasks that require them to

800 J. G. Foy, V. A. Mann

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assign speech sounds to phonemic categories in tests of phonemic awareness, but

also in speech perception and production tasks. We are here concerned with the

possibility that speech production may be linked with reading and that speech

production errors, or patterns of them, might be related to reading risk. From a

practical standpoint, primary language tasks such as speech production may be

much easier to administer than secondary language tasks like phonemic awareness;

elicited naming or repeating is far more natural for a child than comparison or

manipulation of phonemes.

Phonological processing skills appear to be linked with the pattern of errors in

phoneme production prior to school entry (e.g., speech errors, Keren-Portnoy,

Vihman, DePaolis, Whitaker, & Williams, 2010; Mann & Foy, 2007; Preston &

Edwards, 2010; Rvachew & Grawburg, 2006; Smith, 2009). Smith found that

children who later developed reading problems (in second grade and beyond) had

used phonologically less complex utterances in spontaneous speech at 30-months

old than children with normal reading development. Recently, Keren-Portnoy and

colleagues showed that speech sound production mastery in 12–24 month old

children was related to stronger memory for phonological sequences. Failure to

master production of the eight consonants that are typically acquired early in

development also associated with deficient phonological awareness in preschoolers

(Mann & Foy, 2007), and developmentally uncommon or atypical (non-develop-

mental) speech errors appeared to be linked with phonological awareness in

preschool children (Mann & Foy, 2007; Preston & Edwards, 2010). The purpose of

the present study was to determine whether these findings extend to children in

kindergarten, which for many children is the gateway into formal reading

instruction.

As a first step, we sought to explore the relationship between speech errors and

early reading skills in kindergarteners, in order to explore whether certain speech

sounds may be especially difficult for children having difficulty learning the

alphabetic principle and developing strong letter knowledge skills. Early identifi-

cation of children at risk for reading problems may allow them to receive treatment

prior to experiencing reading failure. But to determine which speech errors place

children at risk, it is first necessary to establish what normal development is for

kindergarteners. In the largest study of its kind, about 4% of 6-year olds in the

United States were found to have developmentally inappropriate errors in speech

production (Shriberg, Tomblin, & McSweeny, 1999). Interestingly, the authors

found that subgroup differences, for example, gender, ethnic/racial and socio-

economic differences, all interacted with speech errors but these differences were

not examined with respect to the achievement gap well known to affect these

groups. This sample also consisted of very few Hispanic children, who currently

make up the largest subgroup in schools in the United States.

In the present study, we examined whether the presence, frequency, and type of

speech errors is related with early reading achievement. We have previously shown

that preschool children with strong speech production skills (e.g., no speech errors)

have superior phonological awareness skills compared to children who do make

speech errors (Mann & Foy, 2007). Mody (2003) has proposed that children with

strong phonological production skills have phonological representations that are

Speech deficits and early reading risk 801

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more fully specified (including in articulatory detail) than children who have weaker

speech production skills. This suggests that we should see delays in typical speech

production development among children at risk, and atypical speech production

skills may be an early indicator of a lack of distinctiveness in phonemic

representations among children beginning to read. Both patterns have been

observed among preschool children (Mann & Foy, 2007; Preston & Edwards,

2010; Rvachew & Grawburg, 2006).

Immature speech skills have an obvious effect on phonemic awareness, but they

may also penalize the learning of letter names. Letter names appear to be especially

important in the early stages of learning to read (Foy & Mann, 2006; Treiman,

Sotak, & Bowman, 2001). The current speech production norms indicate that by age

6, children are expected to have mastered speech production of the major

consonants and vowels (Shriberg et al., 1999). However, fricatives, affricates,

liquids and consonant clusters may still be a problem and this has implications for

the learning of letter names in American English: With the exception of W, which

cannot be characterized by one phoneme type, five letter names involve fricatives

(C, F, S, V, Z), three involve affricates (G, H, J), three involve liquids, and glides (L,

R, W), and two involve clusters (Q, X). In short, nearly half the letter names of

consonants in English involve phonemes that are later developing, and it is not

unreasonable to assume that children who have not mastered the production of the

major consonants in English will have a more difficult time producing letter names,

and thus more difficult associating letter sounds with them.

Likewise, if children have difficulty producing speech sounds in certain syllable

positions, we might expect that this difficulty might be reflected in letter name

production. For example, 38% of letter names in English involve consonants in final

position in words (F, H, L, M, N, R, S, X).

Relation between speech, vocabulary, and working memory

Accurate speech production is an aspect of expressive vocabulary, another language

skill that appears to be related to reading, and may be a critical factor in how well

children respond to early reading intervention (Al Otaiba & Torgesen, 2007). In

preschoolers, expressive vocabulary knowledge is highly correlated with early

reading skills such as rhyme awareness, phonemic awareness, and letter knowledge

(Mann & Foy, 2003). This should come as no surprise given that letter knowledge is

tied to reading ability and letter sounds and names, after all, are a set of vocabulary

items that a child must master in order to understand how the alphabet works.

Expressive vocabulary is predictive of response to reading intervention beginning in

preschool (Hindson, Byrne, Fielding-Barnsley, Newman, & Hine, 2005) and first

grade (Berninger et al., 2002; Mathes et al., 2005). Vocabulary also relates to the

effects of book-related talk during shared book-reading in preschoolers (Hindman,

Connor, Jewkes, & Morrison, 2008). Thus, expressive vocabulary, as a component

of oral language skills, may be linked with early reading skills, speech production

abilities, and letter knowledge.


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Another cognitive skill that appears important to reading skills development is

working memory. Whereas short term memory involves capacity aspects of

memory, such as reciting back a series of digits, working memory involves active

manipulations of new material, such as when a child is asked to repeat a series of

digits backwards, or performing several cognitive calculations simultaneously while

temporarily keeping material in memory. Working memory is thought to consist of

independent but interacting component processes. For example, Baddeley (1986,

2003) proposed that working memory consists of a central executive responsible for

supervising and coordinating allocation of resources, a phonological loop for the

processing of auditory information, a visuo-spatial scratch pad for processing visual

information, and an episodic buffer linking this information chronologically.

Working memory undergoes considerable development in early childhood, in

particular the executive function component (Diamond, 2005). Learning disabilities

(Gathercole & Pickering, 2001; Henry, 2001) in general, and reading disabilities

specifically (Leather & Henry, 1994; Swanson & Jerman, 2006), may be associated

with problems with the central executive component of working memory. The

phonological loop component of working memory appears to drive vocabulary

development until school age (Gathercole, Willis, Emslie, & Baddeley, 1992), and

has been shown to predict response to early intervention in preschool children at

familial risk for reading problems (Hindson et al., 2005). Dyslexic children and their

affected parents show independent deficits in both the phonological loop and in the

executive function components of working memory (Berninger et al., 2006). In the

present study, short-term memory (repeating digits) and working memory (reciting

the digits backwards) were examined as possible associates of early reading

impairment. In a separate study, we will be looking at executive function components

and their relation to emergent reading skills.

The goal of the present study is to link speech error patterns to reading risk

measures in kindergarten in order to provide guidance for early identification

practices. Specifically, we sought to explore the following research questions:

(a) Is there a pattern of speech errors that distinguishes kindergarten children at

risk for reading problems from children not at risk at the beginning of the

school year?

(b) Are speech errors and reading risk also linked at year-end, after formal

instruction and any intervention have proceeded?

(c) Do speech errors bear a relation to letter name errors, given the density of

later-maturing phonemes in the letter names?

(d) Are speech errors linked with vocabulary and working memory abilities?

Method

Participants

Participants included 92 kindergarten children (Mage = 5.2 years, SD = .30,

range = 4.6–5.7 years at the beginning of the school year, 47 boys and 45 girls)


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from classes as part of a larger intervention study targeting at-risk children in four

schools in the Los Angeles area that have large proportions of low income children

(see Fig. 1). These schools have a history of being in the lower deciles on state-

sponsored testing and were sites for an intervention study that will be described in a

separate study including children whose primary language was not English and/or

who were fluent speakers of another language. The ethnic composition at the

schools is typical of the ethnic diversity of elementary schools in the Los Angeles

area: 41% Hispanic, 32% Black, 13% Mixed Race, 11% White, and 3% Asian. Only

children whose primary language was English, whose parents reported that they

were not fluent speakers of another language other than English, and were not

receiving special educational service, including speech therapy, through the school

(i.e., did not have an active Individualized Education Plan) at the time of the study

were included in the present study.

Eligible Children*: Researchers obtained parental

consent for participating in study and intervention (if needed)

32 children in need of intensive intervention

(according to DIBELS)

Second month of school to last month of school

Intervention No intervention

11 children achieved benchmark (on DIBELS)

First month of school

Testing T1

47 children in need of strategic intervention

(according to DIBELS)

Teachers recommended 16 children for intervention

Teachers recommended 31 children plus 2 late-comers not receive intervention

Testing T2 Last month of school

Fig. 1 Flowchart illustrating design. *Eligibility criteria: English is primary language, not fluentspeakers of another language, not being considered for, or receiving special educational services(Individualized Education Plan), normal vision and hearing


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Materials

Early reading skills

The determination as to which children were at risk for later reading problems and

candidates for intervention (see below) was made using The Dynamic Indicators of

Basic Early Literacy Skills test (DIBELS, Compton, 2006; Kaminski & Good,

1996). DIBELS is a set of standardized, individually administered measures that is

available free to registered users. DIBELS measures that are appropriate for

kindergarten assessment at the beginning of the school year are letter naming

fluency (LNF) and initial sound fluency (ISF) at the first benchmark testing (within

the first month of school). In the LNF task, the children are asked to name letters

arranged in random sequence; the number correctly identified in 1 min yields the

score. Children are not penalized for articulation errors on this task. In the ISF task,

children are asked to point to one of four pictures on a series of pages that begin

with a specified phoneme and for ¼ of the responses on each page, the child is asked

to provide the initial phoneme for a specific picture.

DIBELS testing yields scores that correspond to labels such as low risk, some

risk and at risk; or established, emerging, and deficit (University of Oregon, n.d.).

Using decision rules based on the calculated odds of achieving grade level

performance given current levels of performance, also available at this site, the

protocol recommended by DIBELS is that each child be placed in one of three

categories: (a) in need of no additional intervention (benchmark), (b) in need of

strategic intervention (strategic) due to low performance on either ISF or LNF, or

(c) in need of intensive intervention (intensive) due to low performance on both the

ISF and LNF subtests. In the present study, 11 children achieved benchmark, 47

were in need of strategic intervention, and 32 in need of intensive intervention

according to DIBELS. Children in the second categories (in need of strategic or

intensive intervention services according to DIBELS) are hereafter referred to as

at-risk. Details of the sample and procedures are provided in Fig. 1. Performance of

each group is summarized in Tables 1 and 2 where it may be seen that the ‘strategic’

and ‘intensive’ groups are comparable to each other and different from the

‘benchmark’ group in cases where the ‘at risk’ group differs from the ‘benchmark’

group.

Intervention

All children in the intensive group received intervention, and the teachers helped to

make final decisions about which children in the strategic group received immediate

intervention and which were placed on a wait-list and monitored. In the present

study, 48 children received intervention by the end of the year, none of whom left

before the school year ended, and 44 children did not receive extra help beyond

standard practices within the classroom upon recommendation of their teachers (see

Fig. 1). Although effects of the intervention are not the focus of this paper, the

results are reported in Appendices 1–3, and are consistent with previous reports of


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significantly improving early reading skills (Foy, 2009). The intervention included

children whose primary language was not English and who spoke another language

fluently, although these children were excluded from the present study (see

eligibility criteria for inclusion in this study in Fig. 1). Children who received the

intervention participated in 1:1 tutoring three times a week for 40 min by trained

tutors using evidence-based practices (Foy, 2009) for 20 weeks over the course of

the school year. The intervention was play-based; each session involves games and

fun activities that are based on letter names, letter sounds, sight word fluency,

phonemic awareness, and concluded with dialogic reading of age-appropriate

books.

Testing

In addition to the screening measures administered to all children whose parents

provided consent, at the end of the school year following the 20 week intervention

period, all children were administered the letter naming (LNF), phoneme

segmenting (PSF), letter sounds (nonwords: NWF), and words read correctly

(WRC) fluency subtests. At the beginning and end of the school year, the children

were also asked to complete the Word Identification (real words) and Word Attack

(pseudowords) subtests of Woodcock-Johnson (WJ) Reading Battery with reliability

Table 1 Reading-related scores (means and standard error) for children who were eligible for inter-

vention (need strategic or intensive intervention according to DIBELS) compared to children who

achieved benchmark on T1 DIBELS measures

DIBELS category

Eligible for intervention

Strategic Intensive Total Benchmarked

n = 47 n = 32 n = 76 n = 11

Beginning of the year

DIBELS ISF 5.10 (.56) 2.53 (.39) 4.02 (.39)*** 25.64 (2.35)

DIBELS LNF 16.23 (1.69) 2.00 (.40) 10.24 (1.28)*** 33.27 (5.18)

WJ words .27 (.09) .38 (.19) .32 (.10)*** 6.09 (1.75)

WJ nonwords 0 (0) 0 (0) 0 (0)*** 4.73 (2.11)

End of the year

DIBELS LNF 41.74 (1.92) 40.67 (2.79) 41.32 (1.59)*** 60.18 (3.46)

DIBELS PSF 30.96 (2.08) 27.23 (2.98) 29.49 (1.72)** 40.45 (3.10)

DIBELS NWF 28.04 (2.03) 27.77 (3.32) 27.93 (1.78)*** 58.63 (8.15)

DIBELS WRC 3.18 (.68) 5.07 (1.11) 3.92 (.61)*** 15.09 (3.42)

WJ words 5.98 (.59) 6.07 (.86) 6.01 (.49)*** 13.91 (2.01)

WJ nonwords 3.82 (.68) 3.29 (.66) 3.62 (.49)*** 8.91(2.00)

Children who were eligible for intervention at the beginning of the year according to DIBELS were

significantly different on this measure from children who had benchmarked on DIBELS

* p \ .05; ** p \ .01; *** p \ .001


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Table 2 Speech errors for children who were eligible for intervention (need strategic or intensive

intervention according to DIBELS) compared to children who achieved benchmark on T1 DIBELS

measures

DIBELS category



n = 47 n = 32 n = 76 n = 11


Speech errors

Total speech errors 7.13 (.93) 8.81 (.128) 7.82 (.76)* 5.09 (2.53)

Age of acquisition errors

Early-8 .18 (.07) .31 (.10) .28 (.08) .25 (.21)

Middle-8 1.34 (.23) 1.16 (.19) 1.26 (.15)** .73 (.63)

Late-8 3.75 (.50) 4.41 (.58) 4.03 (.38)* 2.09 (.72)

Syllable position errors

Prevocalic 8.30 (1.21) 10.05 (1.36) 9.04 (.91) 7.11 (2.95)

Intervocalic 8.90 (1.17) 9.90 (1.36) 9.32 (.88)** 4.17 (2.25)

Postvocalic 5.87 (.87) 5.51 (.91) 5.71 (.63) 3.03 (1.16)

Manner of production errors

Nasals 2.37 (.74) 2.34 (.88) 2.30 (.56) 0 (0)

Stops 1.14 (.56) 1.74 (.58) 1.39 (.40) 1.51 (.78)

Fricatives 15.91 (2.00) 17.43 (2.16) 16.55 (1.47)** 5.94 (1.83)

Affricates 4.92 (2.21) 4.17 (1.50) 4.61 (1.42) 13.63 (9.22)

Liquids 6.06 (1.96) 9.38 (2.69) 7.46 (1.61) 7.57 (6.10)

Glides 1.14 (.79) 2.34 (1.31) 1.65 (.72) 2.27 (2.27)

Clusters 9.63 (2.21) 15.28 (3.60) 11.97 (2.00) 10.69 (7.52)

Error type

Substitutions 6.57 (.87) 7.84 (1.12) 7.11 (.69)** 3.27 (1.44)

Omissions .25 (.08) .38 (.13) .31 (.07) .27 (.19)

Additions .11 (.05) .16 (.07) .13 (.04) 0 (0)

Simplifications .31 (.21) .44 (.19) .37 (.14) 1.55 (1.26)

Reading-related measures

Digits-forward 4.76 (.23) 4.07 (.41) 4.48 (.22)*** 6.70 (.34)

Digits-back 1.24 (.22) .70 (.20) 1.03 (.16)*** 3.00 (.26)

Expressive vocabulary 53.40 (1.63) 45.07 (1.74) 50.06 (1.28)*** 71.60 (3.02)

End of the year

Speech errors

Total speech errors 6.77 (.79) 7.10 (.95) 6.90 (.60)** 2.11 (.81)


Early-8 .13 (.05) .10 (.06) .11 (.04) .11 (.11)

Middle-8 1.03 (.25) .93 (.16) .99 (.16) .33 (.24)

Late-8 3.50 (.37) 3.93 (.57) 3.69 (.32)** 1.00 (.55)


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reported to range from .87 to .97 (Woodcock, 1987). The tests were administered in

random order at both testing periods (T1 and T2).

Speech production

The Sounds-In-Words subtest of the Goldman-Fristoe Test of Articulation-2 (GFTA,

Goldman & Fristoe, 2000), a standardized test of articulatory skill, was administered

to each child, with the responses transcribed phonetically on-line, tape-recorded, and

later analyzed. The test contains 35 simple color stimulus pictures intended to elicit

44 responses. Internal reliability reported by the authors is .96 for females, and .94

for males. Test–retest reliability is .98 for initial, medial, and final sounds. Median

percentages of inter-rater agreement for initial, medial, and final sounds are reported

Table 2 continued

DIBELS category



n = 47 n = 32 n = 76 n = 11


Prevocalic 5.68 (.90) 7.42 (1.06) 6.43 (.69)* 2.53 (1.10)

Intervocalic 9.38 (1.11) 9.83 (1.23) 9.57 (.82)** 2.78 (1.21)

Postvocalic 8.03 (1.14) 7.19 (1.08) 7.67 (.79)** 1.75 (.88)


Nasals 2.19 (.88) 2.08 (.87) 2.14 (.62) 2.78 (1.84)

Stops .28 (.19) 0 (0) .16 (.11) 0 (0)

Fricatives 15.95 (1.85) 18.42 (2.61) 17.07 (1.53)** 3.70 (2.61)

Affricates 9.58 (3.52) 5.00 (1.42) 7.62 (2.11) 0 (0)

Liquids 5.42 (2.42) 7.78 (2.22) 6.43 (1.67) 0 (0)

Glides 3.75 (2.11) 3.33 (2.32) 3.57 (1.55) 5.56 (5.56)

Clusters 9.85 (2.02) 11.57 (2.84) 10.59 (1.67) 3.92 (2.19)

Error type

Substitutions 5.88 (.76) 6.13 (.81) 5.99 (.56)** 1.78 (.85)

Omissions .20 (.06) .13 (.08) .17 (.05) 0 (0)

Additions .23 (.08) .17 (.07) .20 (.06) .22 (.15)

Simplifications .18 (.13) .40 (.16) .27 (.11) .11 (.11)

Reading-related measures

Digits-forward 5.50 (.32) 5.27 (.27) 5.41 (.22) 7.38 (.60)

Digits-back 2.07 (.23) 1.87 (.25) 1.99 (.17)** 4.00 (.38)

Expressive vocabulary 61.70 (1.77) 54.38 (2.99) 59.18 (1.60)** 79.75 (2.97)

Children who were eligible for intervention at the beginning of the year according to DIBELS were

significantly different on this measure from children who had benchmarked on DIBELS

* p \ .05; ** p \ .01; *** p \ .001


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at 93, 90, and 90, respectively (http://ags.pearsonassessments.com/assessments/

technical/gfta.asp).

The responses elicited from the children were audiotaped and phonetically

transcribed by a licensed and certified speech-language pathologist. The samples

were then rechecked by the researcher or a research assistant using the audiotapes.

Any differences between the transcript analyses were resolved through repeated

listening to the taped response. Twenty percent of the transcripts were randomly

selected for analysis by an independent research assistant blind to the research

hypotheses. The percentage of agreement of the consonants transcribed for each

word was calculated. The average percent of agreement for the transcripts was

97.6% (range 95.2–100%).

Speech error analysis

Speech errors were analyzed according to syllable position, target consonant

production manner, error type, and developmental sequence.

Syllable position. On the English GFTA, 22 of the targeted phonemes are

prevocalic, 20 are intervocalic, and 19 are postvocalic (Williams, 2001). Proportion

of errors per syllable position was calculated by summing the errors for that

position, and dividing by the number of targets for that position, and converting to a

percentage.

Manner of articulation. On the GFTA, not all target phonemes are elicited with

equal frequency: 8 targets are nasals, 19 are stops, 20 are fricatives, 6 are affricates,

6 are liquids, and 2 are glides, and a total of 17 clusters (modified from Williams,

2001). Errors for each manner type were calculated as a percentage of each of these

totals by summing the errors for that manner type and dividing by the number of

targets and converting to a percentage.

Type of Error. Each error was classified as an omission (omission of a singleton

consonant), substitution (substitution of a singleton consonant), addition (addition of

a consonant to a singleton consonant), or cluster simplification (omission of one

phoneme from a cluster) following Porter and Hodson (2001). We also included an

error category of additions (addition of a phoneme). Unlike Porter and Hodson who

excluded some substitutions as errors, we scored all substitutions of phonemes as

errors, including substitutions of /θ/ and /∂/ (lisps) for /s/ and /z/ (after Mann & Foy,

2007).

Developmental sequence

Shriberg (1993) identified a normal developmental sequence for acquisition of

consonantal phonemes based on clustering in a rank-ordered sequence of percent

correct consonants in speech-delayed children. These are the Early-8 (/p/, /b/, /j/, /n/,

/w/, /d/, /m/, /h/), Middle-8 (/t/, /η/, /k/, /g/, /f/, /v/, /t∫/, /dʒ/ /l/), and the Late-8 (/∫/,/s/, /θ/, /δ/, /r/, /z/, /ʒ/, /l/). Errors made on the Early-8 sounds (Early-8 errors),

Middle-8 sounds (Middle-8 errors), and Late-8 sounds (Late-8 errors) were

subjected to separate analyses. Children were classified as advanced if they made no


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http://ags.pearsonassessments.com/assessments/technical/gfta.asp

http://ags.pearsonassessments.com/assessments/technical/gfta.asp

errors in consonant production (GFTA), typical if they made no errors on Early-8

sounds but at least one error on middle or later sounds, and delayed if they made at

least one error on the Early-8 sounds, and one or more errors on middle or late

sounds (after Mann & Foy, 2007). Most children (77.2%) made no errors on Early-8

consonants, 38% made no Middle-8 errors, and 13% made no Late-8 errors. A few

children (8.9%) made no speech errors at all.

The delayed (Mage = 5.12 years, SD = .26, range = 4.6–5.55 years), typical

(Mage = 5.19 years, SD = .32, range = 4.6–5.19 years), and advanced (Mage =

5.1 years, SD = .21, range = 4.81–5.49 years) groups did not differ significantly in

age. Age was not significantly correlated with any of the major variables in this study.

Working Memory. The digit span subtest of the Wechsler Intelligence Scale for

Children (Wechsler, 1992) was administered to assess verbal short term and

working memory. In this standardized, reliable, and valid test, the examiner says

single digits at the rate of one per second, and asks the participants to repeat them

forwards (Digits-F) and backwards (Digits-B). Digits-B was used as a measure of

working memory, consistent with views that this is a more reliable measure of

working memory than digits forward (Carroll, Snowling, Hulme, & Stevenson,

2003; Savage, Cornish, Manly, & Hollis, 2006). The Digits-B subtest has also been

shown to be a reliable predictor of reading performance (Gathercole & Pickering,

2001).

Expressive Vocabulary. Expressive vocabulary was measured with the Expres-

sive Vocabulary Test-2 (EVT, Williams, 2006), an un-timed test that has high

reliability and validity (Rathvon, 2004). The examiner asks the participant to label

pictures and to generate synonyms for test words that are presented as a spoken

word accompanied by a picture. Scores indicate the number of correct answers

between basal and ceiling items.

Procedure

The children were tested individually in a quiet room at the beginning and end of the

school year in two sessions lasting about 20–30 min each, as illustrated in Fig. 1.

Results

Before analysis, the data were examined for missing values, fit between their

distributions and the assumptions of multivariate analysis, which were met

(Tabachnick & Fidell, 2001). To correct for the positive skewness and kurtosis in

most of our measures, we used nonparametric statistics (Kruskal–Wallis and

Friedman analyses, and Spearman correlations) to examine relationships between

variables. These tests are appropriate statistics to use when variables have

equivalent but non-normal distributions (Norusis, 2000). Regression analyses were

used to examine predictive relations between speech production measures and our

reading related-measures.


123

Research question (a): is there a pattern of speech errors that distinguishes

kindergarten children at risk for reading problems from children not at risk

at the beginning of the school year?

Speech error analysis

As a first step, we describe the speech errors in our sample according to

developmental sequence, syllable position, manner of speech production, and type

of error in order to gain an understanding of typical versus atypical speech

production performance in kindergarten-aged children.

Developmental sequence. As Fig. 2 shows, the majority of children in the sample

(71.1%) were typical in speech production, with 20% classified as delayed, and

8.9% as advanced.

A Friedman test showed that there were significant differences between errors in

the developmental sequence (χ2 = 103.60, p= .0001), with the children in the entire

sample making significantly fewer errors on Early-8 than Middle-8 sounds (Z= 5.17,

p = .0001) and Late-8 sounds (Z = 7.56, p = .0001), as well as significantly fewer

errors on Middle-8 than Late-8 sounds (Z = 7.11, p = .0001).

Syllable position. A Friedman Test revealed significant differences between

errors in the various syllable positions (χ2 = 8.90, p = .011). Post hoc Wilcoxon

signed ranks tests demonstrated, as shown in Fig. 3, that the children made

significantly fewer errors on consonant productions in syllable final positions (post-

vocalic) than in pre-vocalic (Z = 3.66, p = .0001) and intervocalic positions

(Z = 4.73, p = .0001).

Manner of articulation. A Friedman test showed that there were significant

differences in errors depending on manner of articulation, (χ2 = 175.65, p = .0001).

In paired Wilcoxon ranks tests, as Fig. 4 shows, the children made significantly

0

10

20

30

40

50

60

70

80

Delayed Typical Advanced

Speech Development Classification

Fig. 2 Percentage of children classified according to developmental sequence


123

more errors on fricatives than on nasals (Z = 6.79, p = .0001), stops (Z = 7.18,

p = .0001), affricates (Z = 5.31, p = .0001), liquids (Z = 4.88, p = .0001), glides

(Z = 5.91, p = .0001), and clusters (Z = 4.21, p = .0001), and more errors on

clusters than on nasals (Z = 4.78, p = .0001), stops (Z = 5.68, p = .0001), affricates

(Z = 3.60, p = .0001), liquids (Z = 3.48, p = .001), and glides (Z = 4.74,

p = .0001). The children also made more errors on affricates than nasals (Z = 3.24,

p = .001) and stops (Z = 4.05, p = .0001), and more errors on liquids than on stops

(Z = 3.74, p = .0001).

Type of error. Friedman tests showed (Fig. 5) significant differences between

error types (χ2 = 190.53, p = .0001). Follow up paired Wilcoxon signed ranks tests

showed than children in this study made significantly more substitution errors than

0

2

4

6

8

10

12

Prevocalic Intervocalic Postvocalic

Syllable Position

Fig. 3 Speech errors grouped by syllable position

0

2

4

6

8

10

12

14

16

18

Nasals

Stops

Fricat

ives

Affrica

tes

Liquid

s

Glides

Cluste

rs

Manner of Production

Fig. 4 Speech errors grouped by manner


123

any other type of error: omissions (Z = 7.75, p = .0001), additions (Z = 7.78,

p = .0001), and cluster simplifications (Z = 7.73, p = .0001), and more cluster

simplifications than omissions (Z = 2.06, p = .039).

Reading risk and speech production errors

In this analysis, children who were determined to be at risk (in need of strategic or

intensive intervention services according to DIBELS scores at the beginning of the

year) were compared to children who achieved benchmark on these early reading

measures. As Table 1 shows, there were significant differences between at-risk and

benchmarked children on every reading measure.

Separate Mann–Whitney U tests further revealed significant differences between

the groups on total numbers of speech errors (U = 247.50, p = .023), Middle-8

sounds (U = 222.00, p = .001), and Late-8 target sounds (U = 263.00, p = .046),

intervocalic errors (U = 209.00, p = .006), fricatives (U = 197.00, p = .004), and

substitutions (U = 217.5, p = .01) at the beginning of the year (Table 2).

Another way in which we examined risk of reading problems and speech deficits

was to conduct Spearman correlations between the two DIBELS measures (ISF and

LNF) and each of the speech error types for the beginning of the year measures. As

Table 3 shows, at the beginning of the school year, ISF was significantly correlated

with fricative errors, r(85) = −.27, p = .014. LNF was also significantly negatively

correlated with total errors, r(85) = −.31, p = .01, errors on Late-8 consonants,

r(85) = −.27, p = .013, intervocalic consonant errors, r(85) = −.30, p = .006,

fricative errors, r(85) = −.24, p = .031, clusters, r(85) = −.22, p = .047, and on

substitutions of consonants, r(85) = −.27, p = .013. Scores on the WJ word reading

subtest were significantly negatively correlated with Late-8 speech errors, r(85) =−.25, p = .03, intervocalic r(85) = −.28, p = .01, postvocalic speech errors,

r(85) = −.26, p = .015, fricative errors, r(85) = −.28, p = .01, and substitutions

0

1

2

3

4

5

6

7

8

Omiss

ions

Additio

ns

Substi

tutio

ns

Simpli

ficat

ions

Type of Error

Fig. 5 Speech errors grouped by type (substitution, omission, addition, or cluster simplification)


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Table 3 Spearman correlations between reading measures (initial sound fluency: ISF, letter naming

fluency: LNF, Woodcock-Johnson word: WJW, and nonword reading: WJNW) and speech errors at the

beginning of the year (T1) and year-end (T2)

T1 Reading measure

ISF LNF WJW WJNW

T1 speech measures

Total speech errors −.14 −.31** −.09 −.21

Age of acquisition

Early-8 .07 .01 .10 .18

Middle-8 −.18 −.20 −.19 −.34**

Late-8 −.17 −.27* −.25* −.21


Prevocalic −.17 −.19 −.14 −.13

Intervocalic −.15 −.30** −.28* −.33**

Postvocalic −.08 −.20 −.26* −.18


Nasal −.17 −.17 −.25 −.14

Stops .09 −.16 .04 .10

Fricatives −.27* −.24* −.28* −.25*

Affricates .03 −.13 .06 −.06

Liquids .13 −.19 −.03 −.14

Glides .03 −.06 −.04 .06

Clusters −.02 −.22* −.20 −.18

Error type

Substitutions −.19 −.27* −.27* −.29*

Omissions .05 −.17 .01 −.01

Additions −.14 −.17 −.20 −.16

Cluster simplifications .13 −.20 −.09 .04

T2 speech measures

Total speech errors −.14 −.26* −.17 −.31**

Age of acquisition

Early-8 −.02 −.09 −.12 .01

Middle-8 −.10 −.25* −.06 −.19

Late-8 −.17 −.25* −.14 −.32**


Prevocalic −.10 −.28* −.03 −.20

Intervocalic −.15 −.27* −.18 −.31**

Postvocalic −.13 −.23* −.15 −.29*


Nasal .04 .02 .14 .05

Stops .12 −.03 −.09 −.06

Fricatives −.20 −.26* −.18 −.35**

Affricates −.13 −.19 −.14 −.19


123

r(85) = −.27, p = .013. WJ nonword reading scores were significantly negatively

correlated with errors on the Middle-8 speech sounds, r(85) = −.34, p = .001,

intervocalic errors, r(85) = −. 33, p = .004, fricative errors, r(85) = −.25, p = .03,

and substitutions, r(85) = −.29, p = .012. Due to the low number (n = 9) of children

who read any nonwords, the results of this correlation involving the WJ scores should

be interpreted with caution.

Research question (b): are speech errors and reading risk also linked

at year-end?

In this analysis, we again compared children who had been at risk for reading

problems at the beginning of the year (in need of strategic or intensive intervention

services according to DIBELS) with children who were not at risk (had

benchmarked at the beginning of the year). Mann–Whitney U tests revealed

(p \ .05) that the at-risk children still had significantly lower scores on reading

measures at the end of the year (see Table 1).1 A Mann–Whitney U test revealed

that children who had been at risk for reading problems at the beginning of the year

made significantly more speech errors at the end of the year (U = 122.00, p = .002),

more Late-8 errors, more prevocalic (U = 189.00, p = .044), intervocalic

(U = 127.50, p = .003) and post-vocalic consonant errors (U = 141.00, p =

.005), more errors on fricatives (U = 101.00, p = .001), and more substitutions

(U = 113.00, p = .002) than children who were not at-risk at the beginning of the

year (see Table 2). Thus the differences between the normal and ‘at risk’ groups were

consistent over time.

In a Spearman correlation, early reading scores at the end of the school year were

significantly correlated with year-end speech errors (Table 4). T2 LNF was inversely

correlated with year-end (T2) speech errors, r(84) = −.22, p = .041, Late-8 errors,

Table 3 continued

T1 Reading measure

ISF LNF WJW WJNW

Liquids −.07 −.22* −.03 −.17

Glides .07 −.01 −.06 .06

Clusters −.01 −.21 −.16 −.14

Error type

Substitutions −.16 −.30** −.18 −.32**

Omissions .02 −.04 .01 −.14

Additions −.01 .11 .09 .03

Cluster simplifications .01 −.14 .03 −.01

* p \ .05; ** p \ .01

1 The at-risk group includes children who received the intervention and those who did not receive

additional help beyond standard classroom practices. Effects of the intervention are summarized in

Appendices 1–3.


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Table 4 Spearman correlations between reading measures (letter naming fluency: LNF, phoneme

segmenting fluency: PSF, nonword fluency: NWF, words read correctly: WRC, Woodcock-Johnson word:

WJW, and nonword reading: WJNW) and speech errors at the end of the year (T2)

T2 reading measure

LNF PSF NWF WRC WJW WJNW

T1 speech measures

Total speech errors −.21 −.03 −.10 −.05 −.11 −.15

Age of acquisition

Early-8 −.09 .17 −.08 .12 .00 −.13

Middle-8 −.21 −.09 −.05 −.14 −.13 −.14

Late-8 −.12 −.01 −.06 −.04 −.09 −.10


Prevocalic −.08 .03 .10 −.03 −.11 −.09

Intervocalic −.20 −.06 −.06 −.04 −.11 −.10

Postvocalic −.17 .00 −.07 −.04 −.11 −.17


Nasals −.14 .01 .04 −.10 −.06 −.05

Stops −.17 −.02 .00 .07 −.16 −.14

Fricatives −.19 −.07 −.07 −.08 −.11 −.12

Affricates −.06 .16 −.10 .05 .07 .11

Liquids −.02 −.08 −.06 −.10 −.02 −.08

Glides −.09 .10 .00 .05 −.06 −.09

Clusters −.20 −.04 −.10 −.02 −.05 −.12

Error type

Substitutions −.17 −.04 −.07 −.07 −.10 −.11

Omissions −.18 −.03 −.15 .06 −.15 −.22*

Additions −.13 −.05 .00 −.04 −.02 −.08

Cluster simplifications −.19 .02 −.14 −.09 −.03 −.14

T2 speech measures

Total speech errors −.22* −.11 −.14 −.15 −.13 −.19

Age of acquisition

Early-8 −.01 .12 .10 .13 −.10 −.07

Middle-8 −.09 .10 −.07 −.10 −.16 −.24*

Late-8 −.24* −.19 −.15 −.21 −.13 −.16


Prevocalic −.20 −.04 −.13 −.02 −.16 −.11

Intervocalic −.22* −.14 −.15 −.15 −.17 −.24*

Postvocalic −.26* −.14 −.17 −.27* −.16 −.24*


Nasals .05 .07 −.04 −.19 −.08 −.08

Stops −.02 −.01 −.10 .02 −.13 −.22*

Fricatives −.27* −.20 −.18 −.14 −.18 −.22*

Affricates −.13 .06 −.10 −.03 −.02 −.11


123

r(81) = −.24, p= .033, intervocalic errors, r(81) = −.22, p= .05, postvocalic errors,

r(81) = −.26, p = .02, fricative errors, r(81) = −.27, p = .017, and substitu-

tions r(80) = −.22, p = .05. WJ nonwords were significantly correlated in Spearman

analyses with Middle-8 errors r(82) = −.24, p = .034, intervocalic r(82) = −.24,p = .034 and postvocalic errors, r(82) = −.24, p = .03, errors on stops r(82) = −.22,p = .05, and fricatives, r(85) = −.22, p = .05, and omissions r(85) = −.23, p = .041.

Predictive relations between reading scores and speech errors

Do T1 reading measures predict T2 speech measures? In a Spearman correlation,

early reading scores at the beginning of the school year were significantly correlated

with year-end speech errors (Table 3). Specifically, T1 LNF was inversely

correlated with year end (T2) speech errors, r(82) = −.26, p = .019, Middle-8

errors, r(79) = −.25, p = .025, Late-8 errors, r(79) = −.25, p = .03, prevocalic

errors, r(79) = −.28, p = .012, intervocalic errors, r(79) = −.27, p = .016, and

postvocalic errors, r(79) = −.23, p = .042, fricative errors, r(79) = −.26, p = .021,

liquid errors, r(79) = −.22, p = .049, and substitutions, r(79) = −.30, p = .008.

WJ nonwords at T1 were significantly correlated with year-end speech errors,

r(79) = −.31, p = .005, Late-8 errors, r(79) = −.32, p = .005, intervocalic,

r(79) = −.31, p = .006, and postvocalic errors, r(79) = −.29, p = .011, and fricative

errors, r(79) = −.35, p = .002, and substitutions, r(79) = −.32, p = .005.

Do T1 speech measures predict T2 reading? As shown in Table 4, omissions at

the beginning of the year were significantly linked in Spearman correlations with

year-end WJ nonwords, r(79) = −.22, p = .049.

Speech error improvements and reading. Improvements in speech errors were

calculated as difference scores for each of the speech error scores. Improvements in

the Late-8 speech sounds for all children in the sample were significantly correlated

with year-end scores in PSF, r(79) = .29, p = .011 and improvements in fricatives

were significantly with year-end scores in PSF, r(79) = .25, p = .029, and NWF,

r(79) = .26, p = .023.

Table 4 continued

T2 reading measure

LNF PSF NWF WRC WJW WJNW

Liquids −.07 −.02 −.08 .07 −.06 −.11

Glides .04 .14 .13 .07 −.02 .10

Clusters −.11 −.01 −.08 .03 .05 −.01

Error type

Substitutions −.22* −.04 −.12 −.14 −.18 −.15

Omissions −.13 −.24* −.19 −.01 −.18 −.23*

Additions −.01 −.05 −.08 −.18 −.14 −.18

Cluster simplifications −.17 −.04 −.19 −.06 −.01 −.05

* p \ .05; ** p \ .01; *** p \ .001


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Research question (c): do speech errors bear a relation to letter naming errors,

given the density of later-maturing phonemes in the letter names?

As shown in Tables 3 and 4, letter naming fluency was significantly correlated with

Late-8 errors r(85) = −.27, p = .013, as well as errors on fricatives at the beginning,

r(85) = −.24, p = . 031, and end of the year, r(79) = −.26, p = .021.

Research question (d): are speech errors linked with vocabulary and working

memory abilities?

In this analysis, we sought to explore the role of vocabulary and working memory in

expressive phonological processing. We conducted three sets of analyses: Begin-

ning of the year (T1) EVT and memory with T1 reading scores, and end of the year

(T2) EVT and memory with T2 reading scores, as well as T1 EVT and memory with

T2 reading scores.

As a preliminary step we showed, using Wilcoxon signed ranks tests, significant

improvements in the entire sample from the beginning of the year for Digits-F

(Z = 4.12, p = .0001), Digits-B (Z = 5.37, p = .0001), and EVT (Z = 6.212,

p = .0001). Mann–Whitney U tests showed that children at risk for reading

problems according to DIBELS (see Table 2) had significantly lower Digits-F

(U = 106.5, p = .0001), Digits-B (U = 100.5, p = 0001), and EVT, (U = 59,

p = .0001) at the beginning of the year and lower scores on EVT at the end of the

year (U = 33, p = .0001) than children who were not at risk. Wilcoxon signed ranks

tests showed that there were significant improvements in Digits-F (U = 4.12,

p = .0001), Digits-B (U = 5.36, p = .0001), and EVT (U = 6.212, p = .0001) from

T1 to T2.

As shown in Table 5, at the beginning of the school year, Digits-F, Digits-B and

EVT were significantly correlated with all reading measures (ISF, LNF, WJ words,

Table 5 Spearman correlations between memory (digits-forward: DF and digits back: DB) and

expressive vocabulary (EVT) and reading scores at the beginning (T1) and end of the year (T2)

T1 T2

DF DB EVT DF DB EVT

ISF .22* .42*** .36** – – –

LNF .45*** .43*** .49*** .29** .33** .44***

PSF – – – .26* .14 .40**

NWF – – – .29** .25* .36**

WRC – – – .15 .12 .30*

WJ words .20 .36** .36** .27** .37** .47***

WJ nonwords .41*** .44** .47*** .20 .31** .46***

* p \ .05; ** p \ .01; *** p \ .001


123

and WJ nonwords), except that the correlation between Digits-F and word reading

did not achieve statistical significance, p \ .05. At the end of the year, Digits-F,

Digits-B, and EVT were significantly correlated with most of the reading measures

(LNF, PSF, NWF, WRC, WJ Words, WJ Nonwords). Digits-F, however, was not

significantly correlated withWRC orWJ nonwords nor was Digits-Back significantly

related with PSF or WRC at the end of the year.

Beginning of the year: contributions of memory and vocabulary to speech-

reading links

To further explore whether the links between speech and reading skills at the

beginning of the school year were associated with vocabulary and memory, we

conducted a series of hierarchical regression analyses. Fricative errors, the most

common type of error, did not account for additional variance in Initial Sound

Fluency (ISF) when EVT and memory (Digits-F and Digits-B) were partialed out.

EVT (β = .42, p = .0001) and Digits-B (β = .23, p = .037) were significantly

associated with ISF, R2 = .40, p = .0001.

When the effects of EVT and memory were partialed out, none of the Letter

Naming Fluency correlates (Late-8 errors, intervocalic consonant errors, fricatives,

substitutions,) were significantly associated with LNF except for clusters, which

were significantly independently associated with LNF scores (β = −.21, p = .019),

R2 Δ = .044, p= 19. EVT (β = .36, p= .002) and Digits-B (β= .26, p= .018) were

significantly associated with LNF, R2 = .39, p = .0001.

Likewise, Middle-8 errors were not significantly linked with WJ nonword scores

when the effects of EVT and memory were partialed out. EVT (β = .43, p = .047)

was significantly associated with LNF, R2 = .30, p = .005.

Year end: contributions of memory and vocabulary to speech-reading links

To further explore whether the links between speech and reading skills at the end of

the school year were associated with vocabulary and memory, we conducted a series

of hierarchical regression analyses on all the associations that were significant in the

first-order correlation analyses. Hierarchical regression first entering digits forward

and digits back and expressive vocabulary, showed that only Late-8 speech errors

(β = −.24, p = .048), R2 Δ = .05, p = .05, and postvocalic errors (β = −.28, p =

.022), R2 Δ = .07, p = .022, were independently related to LNF.

T1 and T2 relations between reading measures and speech errors. Hierarchicalregressions partialing out the effects of T1 memory and vocabulary on relations in

Tables 3 and 4 that were statistically significant in zero-order Spearman correlations

revealed that T1 LNF was independently related to T2 total speech errors (β = −.28,p = .05), R2 Δ = .05, p = .05, errors on clusters (β = −.36, p = .02), R2 Δ = .07,

p = .02, and substitutions (β = −.30, p = .05), R2 Δ = .05, p = .05. T1 speech errors

did not significantly predict any T2 reading measures.


123

Discussion

Typical speech production errors for kindergarteners

In order to study the relation between speech errors and early reading skills, we first

sought to describe speech production patterns in our kindergarten sample. Our

results showed that, despite our focus on children in low-SES areas attending

schools with a history of low achievement, it was quite common for kindergartens in

our sample to make few speech errors. Indeed, 15.2% of the children in the sample

made fewer than two speech errors on the target words during assessment. When

kindergartners did make speech errors at the beginning of kindergarten, they

occurred more frequently on Late-8 sounds than sounds that typically develop

earlier, were more likely for consonants in initial and medial positions than final

(Fig. 3), and more common on fricatives and clusters than speech sounds involving

other manners of production (Fig. 4). Speech errors in our kindergarten sample

typically involved substitutions; omissions, additions, and cluster simplifications

occurred infrequently. We explore below the possible reasons for these error

patterns being relatively common in the speech of kindergarteners.

Developmental sequence. Kindergarteners made relatively fewer errors on the

Early-8 consonants, which include nasals (/n/,/m/) glides, and stops. Shriberg &

Kwiatkowski (1994) have argued that mastery of these Early-8 sounds should occur

by 3 years. We found that errors on Early-8 sounds were pertinent in preschoolers

(Mann & Foy, 2007) but not kindergarteners, suggesting that the Early-8 problems

reported in this prior study were a manifestation of delay and not atypical

development.

Syllable position. At the beginning of kindergarten, the children in this sample

made relatively fewer errors on final sounds than other sounds. This is not a finding

typical of younger children, and may reflect the fact that our kindergarten children

are at an age where they are mastering fricatives, which tend to be mastered in final

position before initial position. At the end of the school year, they made more

speech errors on intervocalic (medial) consonants compared to sounds in other

positions. There is some evidence that medial phonemes are harder and later

developing than at least initial sounds. As for the persistence of medial errors

relative to initial and final, spelling errors are more common in medial and final

position (Stage & Wagner, 1992) and spelling of initial phonemes is more accurate

than in either medial and final position (Treiman, Berch, & Weatherston, 1993).

Anthony and Francis (2005) also report that phonemic awareness is acquired for

initial and final word positions before medial.

Speech sound type. Kindergarteners in our sample made more speech errors on

fricatives (which make up 75% of the Late-8 sounds) and clusters than other speech

sound types. Arguably, fricatives and clusters are motorically more difficult

compared to the other sounds (Kent & Read, 1992), and our findings add to the body

of literature showing the relatively late mastery of fricatives in children who are

primary speakers of English (Mann & Foy, 2007; Shriberg & Kwiatkowski, 1994;

Shriberg, Kwiatkowski, & Gruber, 1994; Smit, 1993a, b). Although fricatives are

easier to sustain than stops, they are relatively less sonorous than nasals, liquids, and


123

glides (Treiman, 1984); and Treiman and her colleagues have shown greater

performance deficits for phonological awareness tasks involving fricatives than for

tasks involving stops (see Treiman, Broderick, Tincoff, & Rodriguez, 1998).

Error Type. Most kindergartners’ speech errors involved substitutions, rather

than omissions or additions when they did make speech errors. All of the additions

in this study involved the addition of /k/ or /g/ to /ŋ/ in the word ring. Almost all

were limited to one classroom, and additions in this classroom increased by the end

of the year, apparently being influenced by the African American Vernacular

English (AAVE) style the teacher was using.

Speech errors and early reading risk

Consistent with the critical age hypothesis (Bishop & Adams, 1990) and its

modified version (Nathan et al., 2004b), we found that children who made no speech

errors tended to have superior early reading skills compared to those who made

frequent speech errors. Children who entered kindergarten at risk for later reading

problems made speech errors that were developmentally normal, but more frequent

than children with typical early reading development. For example, they had higher

rates of intervocalic (medial) consonant errors, errors on fricatives and clusters,

substitutions, and errors on Late-8 consonants than children who were at grade-level

upon school entry. Improvement in speech skills was also linked with stronger

reading skills at the end of the year (whether spontaneous or due to intervention),

suggesting that children’s speech error patterns may be early indicators of difficulty

learning to read.

Our findings add to a growing body of evidence showing a link between speech

sound production and the strength of phonological representations. Specifically, we

found that children with the strongest early reading skills at year-end had improved

the most in production accuracy of the Late-8 sounds (which include a high

proportion of fricatives) and specifically of fricatives. Although none of the studies

conducted to date (Keren-Portnoy et al., 2010; Mann & Foy, 2007; Smith, 2009),

including our own, can provide causal conclusions, collectively they do suggest that

perhaps language use, and, in this case, experience with certain kinds of speech

sound productions, may be associated with robust representations of phonemes

associated with early reading development. Although speech production skills most

likely reflect qualitative aspects of phoneme representations, our findings, combined

with that of other researchers, raise the possibility of great importance to early

reading interventionists, that at least a bidirectional relationship might exist between

expressive speech production experiences and the development of robust receptive

phoneme representations. Such representations would arguably permit easy

mapping of phonemes onto orthographic representations, as is required for children

to learn to read.

Both of the DIBELS tests that were administered to kindergarteners bore a

relationship to speech production errors. Letter Naming Fluency was significantly

correlated with errors on fricatives at the beginning and end of the year, but not the

other singleton phonemes, suggesting that the fricative speech errors may make it


123

harder to name letters fast, as in a timed test such as DIBELS, especially given that

fricatives are involved in proportionally more letter names than other speech

sounds. Unfortunately, the DIBELS LNF task, which was used as the measure of

letter knowledge in the present study, does not randomly assess all letters, and the

time limit (1 min) for the task results in some children completing more letter

productions than others. The test also includes repetition of some letters. These

characteristics of the letter naming task make an analysis of the direct relationship

between speech production of specific sounds and their associated letter names

impossible. Future research, assessing all letter names, may indicate whether the

speech errors were related to letters that contained those speech sounds. At-risk

early readers also made more non-developmental errors than children with typical

early reading skills including higher rates of errors on nasals, additions and

omissions, and these are less directly linked to the speech sounds within letter

names.

Phonemic awareness was also related to speech errors, especially to fricatives and

clusters. In the phonemic awareness task we used (ISF), however, children are only

required to articulate the word including the target sound for a quarter of the items. In

the remainder of the items, the children point to a picture. The relationship between

performance on articulation and sound fluency is thus more abstract, and might be

accounted for by a common reliance on the strength of phonological representation

hypothesized to be a factor in reading readiness (Fowler, 1991; Fowler & Swainson,

2004; Walley, 1993; Walley, Metsala, & Garlock, 2003).

All of these findings suggest that children entering kindergarten with speech

problems may be strong candidates for early reading intervention by virtue of

underlying phoneme processing problems linked to difficulties learning letter names

and their associated sounds. Efforts that result in improved speech skills may also

link with improvements in early reading skills. In particular, numerous speech

errors and non-developmental patterns may be markers of special risk in

kindergarteners.

Vocabulary and working memory correlates of speech production errors

We found considerable evidence for the link between vocabulary, working memory,

and reading proficiency that had been previously reported in the literature

(Gathercole, Alloway, Willis, & Adams, 2006; Gathercole & Baddeley, 1993).

Expressive vocabulary and memory were linked with all of our early reading

measures at the beginning and most of the reading measures at the end of the year.

Children with low scores on phonological awareness and letter knowledge fluency

measures (according to DIBELS) at the beginning of kindergarten had impaired

vocabulary and memory (short-term and working) compared to children who had

grade-level skills upon kindergarten entry.

Given their strong associations with early reading, we expected that at least some

of the variance between speech production skills and early reading would be

explained by expressive vocabulary and memory. Indeed, most of the relations were

no longer significant when these effects were partialed out. Relationships that


123

appeared to be independent of the effects of expressive vocabulary and memory were

the link between errors on clusters of consonants (occur in two letter names: Q and X)

and letter naming fluency at the beginning of the year, and the link between Late-8 and

post-vocalic errors and letter naming fluency at the end of the year. Given that about

40% of letter names in the English alphabet involve Late-8 developing consonants

and 38% involve postvocalic consonantal speech sounds (F, H, L, M, N, R, S, X),

these findings suggest that speech errors that are considered to be developmentally

appropriate for kindergarteners may nonetheless be associated with difficulty learning

letters during kindergarten. Phonemic awareness and speech production skills

appeared to share variance with expressive vocabulary and memory abilities,

although all of these measures showed improvements over the course of the year. A

further implication of our study, consistent with a growing body of evidence linking

working memory to reading skill (e.g., Savage, Lavers, & Pillay, 2007), is that efforts

to improve vocabulary andworkingmemory in children entering kindergartenmay be

especially effective in maximizing children’s achievement of early reading skills.

Whereas changes in working memory are clearly affected by age (e.g., Gilchrist,

Cowan, & Naveh-Benjamin, 2009), aspects of working memory may be modifiable

by experience (Dahlin, Neely, Larsson, Backman, & Nyberg, 2008; but see Engel,

Sanos, & Gathercole, 2008; Klingberg et al., 2005) and thus by intervention and

classroom experiences. Our findings suggest that individual differences in vocabulary

and memory play a major and perhaps reciprocal role in the development of early

reading and expressive phonological skills.

Limitations of our study suggest that future research is warranted. Our sample

tended to consist of children with very low early reading skills upon kindergarten

entry: We might expect a different patterns of results in children with stronger letter

knowledge, phonemic awareness, and oral language skills as presumably these

children would have more robust phonological representations, and may show

different patterns of speech production errors linked to later literacy skills. The fact

that only 11 children achieved benchmark may limit our ability to generalize, as does

the fact that some of the ‘at risk’ children did not receive interventions. Yet we are

encouraged by the fact that, despite such noise in our subject pool, we did observe

strong and significant differences between benchmark children and children at risk.

Our study also only focused on a single year of schooling, whereas future research

might explore associations between speech production skills and reading performance

in grades one and beyond, and the specific effects that intervention, and type of

intervention, may have on literacy and speech outcomes. The weak to moderate

effects, while statistically significant, also suggest the need for replication. As we

mentioned previously, our use of the DIBELS limited our ability to see the relation

between specific letters and articulation of the phoneme they represent. In future work

we will use an exhaustive test of letter knowledge to permit a more comprehensive

analysis. Also, our measure of vocabulary was an expressive measure and as such

involved some of the same skills as our test of speech production. Expressive

vocabulary was one of the stronger correlates in our study and in the literature in

general. Future work that tries to remove the confound of vocabulary might do well to

include receptive vocabulary as another measure that would not share the demand on

articulation.


123

In conclusion, the present study provides evidence that speech production errors

in children entering kindergarten, even if developmentally appropriate, may

possibly be early markers of later difficulty learning to reading. Mastery of

fricatives may be especially important for children learning the letters of the English

alphabet, but the presence of fricatives in the letter names is not the sole reason why

children prone to speech production errors are also prone to reading difficulties. Due

to the entanglement of speech production skills, vocabulary, and memory with the

developmental of early reading skills, children entering kindergarten with weak

early reading skills may benefit from teaching practices and intervention programs

that strengthen speech, expressive vocabulary, and memory as well as phonemic

awareness and letter knowledge.

Acknowledgments The authors would like to thank the parents, children, teachers and schooladministrators who made this research possible. We also gratefully acknowledge the assistance of thefollowing Loyola Marymount University students with data collection, transcription, scoring, data entry,and reliability assessments: Brent Cannons, Karla Dhungana, Vanessa Loaiza-Kois, and Rachelle Reeder.

Open Access This article is distributed under the terms of the Creative Commons AttributionNoncommercial License which permits any noncommercial use, distribution, and reproduction in anymedium, provided the original author(s) and source are credited.

Appendix 1

See Table 6.

Table 6 Reading-related scores (means and standard error) for the eligible children (according to

DIBELS) who received intervention and did not receive intervention at the beginning and end of the year

Eligible (DIBELS) for intervention

Received intervention No intervention

n = 46 n = 25


DIBELS LNF 5.30 (.92)*** 19.44 (2.5)

DIBELS ISF 3.38 (.45)** 5.43 (.74)

Woodcock-Johnson words .35 (.15)* .28 (.10)

Woodcock Johnson nonwords 0 (0) 0 (0)

End of the year

DIBELS LNF 41.76 (1.74) 42.56 (3.44)

DIBELS PSF 32.22 (2.09) 27.52 (3.10)

DIBELS NWF 29.11 (2.32) 27.80 (3.06)

DIBELS WRC 4.70 (.80) 3.08 (1.06)

Woodcock-Johnson words 6.21 (.63) 5.72 (.77)

Woodcock Johnson nonwords 3.67 (.52) 4.08 (1.08)

Children in intervention and no-intervention groups were significantly different on this measure

* p \ .05; ** p \ .01; *** p \ .001


123

Appendix 2

See Table 7.

Table 7 Reading-related scores and speech errors for the children who received the intervention and did

not receive the intervention at the beginning and end of the year



n = 46 n = 25


Digits-forward 4.26 (.31)*** 5.05 (.29)

Digits-back .65 (.15)*** 1.67 (.34)

Expressive vocabulary 46.98 (1.44)** 56.42 (2.24)

Speech errors


Early-8 28 (.08) .16 (.09)

Middle-8 1.40 (.20)** 1.08 (.27)

Late-8 4.91 (.48)* 2.60 (.54)


Prevocalic 10.64 (1.7) 6.43 (1.42)

Intervocalic 11.17 (1.11) 6.43 (1.34)

Postvocalic 6.89 (.80) 3.97 (.98)


Nasals 2.39 (.73) 2.50 (1.02)

Stops 1.54 (.60) .89 (.42)

Fricatives 19.97 (1.92)** 11.23 (1.99)

Affricates 5.32 (1.76) 3.33 (2.72)

Liquids 8.87 (2.20) 5.33 (2.49)

Glides 2.70 (1.14) 0 (0)

Clusters 13.39 (2.68) 9.41 (3.26)

Error type

Substitutions 8.62 (.93)** 4.68 (.93)

Omissions .36 (.10) .20 (.08)

Additions .13 (.05) .16 (.07)

Cluster simplifications .28 (.13) .48 (.37)

End of the year

Digits-forward 5.33 (.22) 5.60 (.51)

Digits-back 1.80 (.22)** 2.36 (.28)

Expressive vocabulary 56.13 (2.20)** 63.40 (2.41)

Speech errors


Early-8 .18 (.06) 0 (0)

Middle-8 1.0 (.18) .90 (.35)


123

Appendix 3

See Table 8.

Table 7 continued



n = 46 n = 25

Late-8 4.02 (.51) 2.90 (.50)


Prevocalic 7.77 (.88) 4.32 (1.02)

Intervocalic 9.67 (1.05) 9.29 (1.40)

Postvocalic 8.19 (.92) 5.51 (1.38)


Nasals 2.22 (.82) 1.79 (.98)

Stops .25 (.17) 0 (0)

Fricatives 18.41 (1.98) 12.95 (2.08)

Affricates 7.41 (2.28) 8.73 (5.09)

Liquids 6.67 (1.87) 7.14 (3.91)

Glides 5.56 (2.37) 0 (0)

Clusters 10.85 (2.20) 8.68 (2.55)

Error type

Substitutions 6.43 (.72) 4.95 (.85)

Omissions .16 (.06) .19 (.09)

Additions .20 (.07) .14 (.08)

Cluster simplifications .22 (.10) .24 (.24)


* p \ .05; ** p \ .01; *** p \ .001

Table 8 Year-end DIBELS and Woodcock-Johnson reading scores for eligible children who received the

intervention compared to children who did not receive the intervention, adjusted for memory and

vocabulary differences in the groups at the beginning of kindergarten


Intervention No intervention Effect size

n = 46 n = 25 Cohen’s d

DIBELS

Letter naming fluency 44.94 (1.95)* 36.51 (2.39) .67

Phoneme segmenting fluency 34.76 (2.27)*** 22.03 (2.78) .92

Nonword fluency 31.98 (2.37)* 23.21 (2.90) .57

Words read correctly 5.20 (.82)* 1.88 (1.00) .63

Woodcock-Johnson

Words 6.74 (.62) 4.96 (.76) .44


123

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